Mustafa Bilgic

4.9k total citations · 1 hit paper
44 papers, 2.7k citations indexed

About

Mustafa Bilgic is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Mustafa Bilgic has authored 44 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 7 papers in Statistical and Nonlinear Physics. Recurrent topics in Mustafa Bilgic's work include Machine Learning and Algorithms (15 papers), Machine Learning and Data Classification (10 papers) and Imbalanced Data Classification Techniques (7 papers). Mustafa Bilgic is often cited by papers focused on Machine Learning and Algorithms (15 papers), Machine Learning and Data Classification (10 papers) and Imbalanced Data Classification Techniques (7 papers). Mustafa Bilgic collaborates with scholars based in United States, Türkiye and Israel. Mustafa Bilgic's co-authors include Lise Getoor, Galileo Namata, Brian Gallagher, Prithviraj Sen, Tina Eliassi‐Rad, Raymond J. Mooney, Lilyana Mihalkova, Louis Licamele, Aron Culotta and Matthew A. Shapiro and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Science Advances and PLoS Computational Biology.

In The Last Decade

Mustafa Bilgic

41 papers receiving 2.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Collective Classification in Network Data

2008 1.8k citations Prithviraj Sen, Galileo Namata et al. profile →

Peers

Mustafa Bilgic

AI

SNP

CVPR

IS

CNC

Galileo Namata United States

Kuansan Wang United States

Prithviraj Sen United States

Sen Wu China

Yanghua Xiao China

Mohammad Al Hasan United States

Andrew Kachites McCallum United States

Jason D. M. Rennie United States

François Fouss Belgium

Galileo Namata United States

Mustafa Bilgic

2.0k ×0.9

AI

908 ×1.1

SNP

460 ×0.9

CVPR

393 ×0.8

IS

202 ×0.8

CNC

Citations per year, relative to Mustafa Bilgic Mustafa Bilgic (= 1×) peers Galileo Namata

Countries citing papers authored by Mustafa Bilgic

Since Specialization

Citations

This map shows the geographic impact of Mustafa Bilgic's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mustafa Bilgic with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mustafa Bilgic more than expected).

Fields of papers citing papers by Mustafa Bilgic

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mustafa Bilgic. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mustafa Bilgic. The network helps show where Mustafa Bilgic may publish in the future.

Co-authorship network of co-authors of Mustafa Bilgic

This figure shows the co-authorship network connecting the top 25 collaborators of Mustafa Bilgic. A scholar is included among the top collaborators of Mustafa Bilgic based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mustafa Bilgic. Mustafa Bilgic is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Rashid, Mudassir, et al.. (2025). Cyber–physical–human systems in precision medicine: Advances in artificial pancreas for treatment of diabetes. Annual Reviews in Control. 60. 101033–101033.

2.

Rashid, Mudassir, et al.. (2025). Stochastic Model Predictive Control of Blood Glucose Levels using Probabilistic Meal Anticipation. IFAC-PapersOnLine. 59(2). 49–54.

3.

Bilgic, Mustafa, et al.. (2023). Context-Aware Feature Selection and Classification. 4317–4325.

4.

Matthews, J., Sara Saheb Kashaf, Rakefet Ben-Yishay, et al.. (2022). OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics. PLoS Computational Biology. 18(11). e1010584–e1010584. 68 indexed citations

5.

Balasubramanian, Siva K., et al.. (2022). Leaders or Followers? A Temporal Analysis of Tweets from IRA Trolls. Proceedings of the International AAAI Conference on Web and Social Media. 16. 2–11. 4 indexed citations

6.

Bilgic, Mustafa, et al.. (2022). Ranking-Constrained Learning with Rationales for Text Classification. Findings of the Association for Computational Linguistics: ACL 2022. 2034–2046. 3 indexed citations

7.

Zawojewski, Judith S., et al.. (2019). Disciplinary Learning From an Authentic Engineering Context. Purdue e-Pubs (Purdue University System). 9(1). 7 indexed citations

8.

Bilgic, Mustafa, et al.. (2016). Active Inference and Dynamic Gaussian Bayesian Networks for Battery Optimization in Wireless Sensor Networks. National Conference on Artificial Intelligence. 5 indexed citations

9.

Akar, Banu, et al.. (2016). Active inference for dynamic Bayesian networks with an application to tissue engineering. Knowledge and Information Systems. 50(3). 917–943. 4 indexed citations

10.

Bilgic, Mustafa, et al.. (2016). Evidence-based uncertainty sampling for active learning. Data Mining and Knowledge Discovery. 31(1). 164–202. 61 indexed citations

11.

Bilgic, Mustafa, et al.. (2014). Dynamic Bayesian network modeling of vascularization in engineered tissues. 89–98. 2 indexed citations

12.

Bilgic, Mustafa, et al.. (2011). Dynamic Processing Allocation in Video. IEEE Transactions on Pattern Analysis and Machine Intelligence. 33(11). 2174–2187. 7 indexed citations

13.

Bilgic, Mustafa, et al.. (2011). Active inference for retrieval in camera networks. 23. 13–20. 6 indexed citations

14.

Bilgic, Mustafa, Lilyana Mihalkova, & Lise Getoor. (2010). Active Learning for Networked Data. International Conference on Machine Learning. 79–86. 95 indexed citations

15.

Bilgic, Mustafa & Lise Getoor. (2009). Link-based Active Learning. Neural Information Processing Systems. 13 indexed citations

16.

Bilgic, Mustafa, et al.. (2009). Efficient Resource-constrained Retrospective Analysis of Long Video Sequences. Neural Information Processing Systems. 1 indexed citations

17.

Kang, Hyunmo, Lise Getoor, B. Shneiderman, Mustafa Bilgic, & Louis Licamele. (2008). Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation. IEEE Transactions on Visualization and Computer Graphics. 14(5). 999–1014. 35 indexed citations

18.

Sen, Prithviraj, Galileo Namata, Mustafa Bilgic, et al.. (2008). Collective Classi!cation in Network Data. 4 indexed citations

19.

Bilgic, Mustafa, Galileo Namata, & Lise Getoor. (2007). Combining Collective Classification and Link Prediction. 381–386. 100 indexed citations

20.

Bilgic, Mustafa & Raymond J. Mooney. (2005). Explaining Recommendations: Satisfaction vs. Promotion. 148 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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